Inter-turn fault detection in PM synchronous motor by neuro-fuzzy technique

Ahouee, Reihaneh Amiri; Mola, Mahmood

doi:10.1007/s13198-020-01019-1

Cited by 7 publications

(1 citation statement)

References 34 publications

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“…In fact, the fault resistance value R f indicates the intensity of the insulation defect. The winding where the fault occurs is therefore split into two parts [30]:…”

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confidence: 99%

PMSM Inter-Turn Short Circuit Fault Detection Using the Fuzzy-Extended Kalman Filter in Electric Vehicles

Romdhane,

Naoui,

Mansouri

2023

Electronics

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To avoid damaging the motor and its surrounding equipment, detecting Inter-Turn Short Circuit (ITSC) faults in Permanent Magnet Synchronous Motors (PMSMs) applied in electric vehicles is a crucial task. In this paper, the detection of ITSC faults in stator winding for PMSMs is carried out by means of the Extended KALMAN Filter (EKF) algorithm combined with the Fuzzy Logic Estimator (FLE). To estimate the motor parameters, including the rotor position and speed, the EKF algorithm uses the measured stator currents and voltages beside the stator resistance, which is calculated in advance using fuzzy logic and fed to the EKF. The change behaviors of the estimated parameters were then used to detect short circuit faults in the PMSM. Using Matlab/Simulink, the proposed FL-EKF algorithm was implemented and tested on a faulty PMSM controlled by Field Oriented Control (FOC). The observation of a perfect estimation of the stator resistance through the simulation helps to precisely detect the failure, and that demonstrates the sensitivity and robustness of the proposed approach.

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“…In fact, the fault resistance value R f indicates the intensity of the insulation defect. The winding where the fault occurs is therefore split into two parts [30]:…”

mentioning

confidence: 99%